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(1)

Creation of CPQRA Data Base

2009_2

nd

semester

En Sup Yoon

(2)

Introduction

Present an overview of the data in CPQRA

Basic information necessary for a CPQRA of new or existing facility

Material information

Process chemistry

Material toxicity

Process flow diagram and P&ID

Control strategy

Operation and maintenance philosophy

Emergency response considerations

Material interactions

Equipment specification

Operating procedure

Maintenance practice

(3)
(4)

Various type of data that should be considered

Equipment failure rate

Toxicity

Human error

Materials of construction

Ignition source

Location-specific data for nearby population

Meteorology

External events

Nearby waterway, road, railroad and airports

(5)

Historical Incident data

May be used directly to estimate top event frequencies

Most of these data sources address major events or failure such as

Leak of toxic materials

Major fires or explosion

Pipeline leaks and rupture

Transportation accidents

Accidents causing fatalities or serious injuries

Data source can be grouped into three categories

Failure mechanisms and cause

Consequence effects

Frequencies of certain types of incidents

(6)
(7)

Process and Plant Data

Plant layout and system description

Process chemistry

Including side reactions under normal and abnormal conditions)

Physical and chemical properties of all process materials

Chemical and material of construction interactions

Process flow diagram

Including process description and specific operating

parameters such as flow rates, pressures, temperature and stream compositions)

Process design basis

Including external events)

Process utilities

Cooling, steam, electricity, instrument air and utility back-up systems

Water treatment system

(8)

Plant layout and system description(cont.)

Equipment specification

Including material of construction

Equipment detail drawings

P&ID

Including utilities and relief systems

Plant layout drawings

Plant and immediate surroundings including elevations

Firewater and drainage drawings

Material properties

Including in-process intermediates

Control logic

Instrument loopsheets, relay logic diagram

(9)

Plant layout and system description(cont.)

Operating instrument

Operating philosophy

Storage inventory levels, operating schedule, staffing, start-up and shutdown, operator training, safety policy

Safety equipment

Fire protection, emergency relief interlock and alarm systems

Historical incident and maintenance records

Maintenance philosophy and program

(10)

Ignition sources and data

The risk for flammable material is dependent on

The chance that the material ignites

The ignition energy

The level of confinement of the released cloud

Typical source of ignition

Flares, Boiler, Fired heaters

Static electricity

Electrical motors, vehicle traffic

Hot work : welding and cutting

Lightning

Overhead high voltage lines

Mechanical : sparks, friction, impact, vibration

Chemical reaction

(11)
(12)

Ignition probability

Typically modeled as a function of two components

The first is the probability the ignition source will be present to ignite the mixture

Presence Factor

The second is the probability that, given the ignite source is present, it is actually ignites the cloud in a given time interval

Strength Factor

Each potential ignition source will have its own unique combination of presence and strength factor

(13)

Typical ranges for on site-strength factors for hydrocarbons

Furnaces, boilers, heaters 0.9-1.0

Substations 0.001-0.3

Office building 0.1-0.2

Truck loading/Unloading area 0.1-0.5

Cars 0.2-0.4

Construction fabrication shop 0.1-0.5

(14)
(15)

Chemical Data

Types of data

Thermodynamic data

Including vapor pressure, boiling point, freezing point, critical temperature and pressure, enthalpies, entropies, specific and latent heats, heat of combustion

Flammability

Flash point and fire point

LFL, UFL

Autoignition temperature

Maximum allowable oxygen content

Minimum ignition energy

Deflagration index for gasses

Burning velocity

Dust explosion data

Maximum rate of pressure rise

Maximum rate in a closed chamber

Layer ignition temperature

(16)

Types of data(cont.)

Industrial hygiene and toxicity data

Short-term exposure data such as LD50, LC50, ERPG’s

Protective equipment needed

Miscellaneous

Chemical interaction and reactivity data

Shock sensitivity

Thermal analysis data

Accelerating rate calorimetry(ARC) data

Vent sizing package(VSP) data

Reaction kinetics and thermodynamic models

(17)

Source

Flammability data

NFPA 325M(1984), Bulletin 627(Zabetakis, 1965), Fire Protection Handbook(cote, 1986)

Dust explosion data

NFPA 68(1994)

Industrial hygiene and toxicity data sources

Threshold Limit Values for Chemical Substances and Physical Agent(1996)

Emergency Response Planning Guidelines(1994)

Pocket Guide to Chemical Hazards(1994)

Chemical reactivity hazards data

Guidelines for Chemical Reactivity Evaluation and Application to Process Design(1995)

(18)

Environmental Data

Population data

Necessary to know the population distribution on and around the site to estimate risk

Generally defined as population density

Source of population data for an area

Census reports

Detailed map

Aerial photographs and site inspection

Typical population density estimates for different categories of occupancy

Urban : 19,000-40,000 people/square mile

Suburban : 5,000-19,000 people/square mile

Scattered housing : 250-5,000 people/square mile

(19)

Meteorological Data

Weather condition

Major effect on the way a release spreads

Generally use typical 16 point wind rose

Generally many risk analysis employ at least two weather condition

Stable (2m/s, Stability F)

Average condition (5m/s, Stability D)

Meteorological data source

Weather data can be obtained from the National Oceanic and Atmospheric Administration(NOAA)

(20)
(21)

Geographic Data

Include local and site maps on a scale adequate to met the CPQRA objective

Aerial photographs, on-site tours and local building characteristics also provide useful information

(22)

Topographic Data

Local topography is important in modeling the dispersion of a gas

Consider large obstacles ranging from trees to mountains and valley

Four types of models which can be used to analyze such release scenarios

Standard EPA Gaussian models that are corrected for plume lifting as the plume approaches the hill

Drainage flow model(for dense gas flow down slopes)

Three dimensional models

Puff trajectory models for nonhomogeneous wind field

(23)

External Event Data

External events are either man-made(aircraft crashes) or natural(earthquake, Floods)

Design data should be obtained on individual critical items(e.g., vessels, pipes, control building, blast wall) to determine their performance under incident conditions

(24)

Equipment Reliability Data

Equipment reliability

Defined as the probability that process equipment will perform its intended function adequately for a

specified exposure period

Three important point about equipment reliability

A probability

A function of the exposure period

A function of the definition of equipment failure

R(t) is reliability as a function of t

F(t) is a cumulative failure distribution as a function of t

t is time

) ( 1

)

( t F t

R = −

(25)

Probability(Failure) density function, f(t)

Substituting (5.5.3) into (5.5.1)

Since the total area under the probability density function, f(t), must be unity, so

dt t t dF

f ( )

)

( = F t =

t f t dt

0

) ( )

(

=

t

dt t f t

R

0

) ( 1

) (

=

t

dt t f t

R( ) ( )

(26)
(27)

Equipment failure rates

Defined for time-dependent and demand dependent exposure periods

Time-dependent equipment failure rate

Demand-dependent equipment failure rate

nD represent the number of demand

failure to

exposed equipment

of pieces of

number

unit time per

failures equipment

of number

(t) = λ

failure to

exposed equipment

of pieces of

number

demand per

failures equipment

of number

) (nD = λ

(28)

Time-related failure rates

Often represent as the number of failures per 106 hr

For equipment which is normally functioning

Running pump, temperature or pressure transmitter

Demand-related failure rates

Typically given as the number of failure per 103 demands

For equipment that is normally static but is called upon at random interval

A switch, a standby generator

(29)

Failure rate versus frequency

Time-related equipment failure frequency can be defined as the number of failure events that occur, divided by the total elapsed calendar time during which these event occur

Time-related equipment failure rate can be defined as the number of failure events that occur, divided by the total elapsed operating time during which these events occur

(30)

Probability of failure rate

Represented by a probability distribution function

Probability distribution function

If the independent variable is time, the probability of time-

related failure at some time-in-service, t, is the probability that the equipment will between t0 and t

This probability approaches 1.0 as the equipment ages (t infinite)

(31)

Using eq.(5.5.6) convert failure rates to probabilities of failure

λ(t) is instantaneous failure rate

f(t) is probability density function of t

R(t)is reliability as a function of t

T is time

From eqs.(5.5.1) (5.5.2) and (5.5.3)

R(T) λ(t) = F(t)

dt t R

t t dR

) (

) ) (

( =

λ

(32)

Eq.(5.5.10) can be integrated and solved for R(t)

Functional form

=

t t dt

t R

0

) ( exp

)

( λ

] ), ( [ )

(t t t

R = Φ

λ

t and (t)

of function on

distributi probaility

is t]

(t),

[λ λ

Φ

(33)

Constant failure rate model

Appropriately used to define the reliability of components which are subject only to failures occurring at random interval

Generally based on the exponential distribution

Reliability of a component in the time interval(0,t)

e is the base of the natural logarithm(2.71828)

λ is the time constant failure rate(1/mean time between failure)

T is operating time for which we want to know the reliability R of the component

e t

t

R( ) = λ

(34)

Complement of the reliability(failure probability)

Pf is the probability of failure of the component in the time interval(0,t)

t

f t e

P ( ) = 1− λ

(35)

Nonconstant failure rate model

The most commonly model is Weibull-distribution- based models

Used to identify the infant mortality, useful

life(constant failure rate) and wear-out modes of failure

Two parameters in Weibull model

Beta parameter(shape parameter)

Determined the shape of the Weibull curve

When the value of shape parameter is greater than 1, the rate of failure increases with time

Alpha parameter(the scale or characteristic life parameter)

Amount the curve is spread out along the abscissa depend on alpha parameter

Expressed in unit of time, typically hours

(36)

Reliability formula associated with the Weibull density function

Formula for estimating failure rate associated with the Weibull density function

β )

e (t/

R(t) = α *

) 1

)(

/ ( )

(t = β α β t β Fr

(37)
(38)

Types and Source of Failure Rate data

Plant specific data

Contain failure rates specific to equipment

Valve or pump in use at a facility by manufacturer, make, model and serial number

Generic data

Less specific and detailed than the data derived from specific equipment failure history

The PERD Guidelines offer an generic data base of equipment failure rate data for use in CPQRA

(39)
(40)
(41)

Key Factors Influencing Equipment Failure Data

Various factors influencing equipment failure rate

Equipment description(type, boundaries, size)

Design standards

Materials of construction

Fabrication technique

Quality control

Installation techniques

Startup practice

Operating strategy

Process medium

Internal environment

External environment

Maintenance strategy

Failure mode

Equipment age

(42)
(43)

Key factors to characterize equipment failure rate(PERD guidelines(AIChE/CCPS)

Equipment description

Process medium

Failure mode

Causes

severity

(44)

Failure modes, causes and severity

Failure rate can be characterized according to the mode, cause and severity of failure

Failure mode

Defines the manner in which a piece of equipment fails to perform its intended function

Failure cause

Describes the condition that cause the faulty performance

Failure severity

Express the extent to which equipment performance is impaired for a given failure mode and cause

(45)
(46)
(47)

Equipment age

The variation of equipment failure rate with time-in- service can be divided into three regions

Burn-in

Often called “infant mortality”. The equipment failure rate is high.

Such failure is usually due to factors such as defective manufacturer or incorrect installation

Normal operation

The equipment failure rate declines during normal operation until a constant rate is reached

Wear-out

The equipment failure rate rises again as deterioration sets in, often described as wear-out failure

(48)
(49)

Failure rate adjustment factors

λ is adjusted equipment failure rate

λg is generic equipment failure rate

fi is adjustment factor i (i=1 to n)

n is number of adjustment factors that apply

=

= n

i

i g

A λ f

λ

1

(50)
(51)
(52)

Collection and processing of raw plant data

Raw failure data collection and processing procedure

Collect and review raw plant data

Classify and sort raw data into taxonomy data cells

Divide and count demand-related and time-related failures

Estimate exposure periods

Screen for zero failures

Screen for trends by failure mode

Calculate failure rates

Determine confidence limits

Reduce the failure rate data set

(53)
(54)
(55)

Preparation of the CPQRA equipment failure rate data set

Procedure for creating the equipment failure rate data segment of a CPQRA analysis data base

Define equipment in CPQRA

Define taxonomy data cells

Determine data accuracy requirements

Identify failure rate models

Collect available data

Construct initial data set

Screen initial data set

Aggregate and smooth available data

Determine sensitivity and uncertainty in the finalized data set

(56)
(57)

Human reliability data

Factors can affect the reliability

Types of task

Environmental conditions

System element and characteristics

Types of system

Quality of human engineering of control and displays

Motivation

Level or perceived psychological stress

Skill and training

Presence and quality of written instructions and methods used

Coupling of human actions

Personal redundancy

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